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FDD3338 Topics in Computer Vision II 6.0 credits

Information per course offering

Course offerings are missing for current or upcoming semesters.

Course syllabus as PDF

Please note: all information from the Course syllabus is available on this page in an accessible format.

Course syllabus FDD3338 (Spring 2019–)
Headings with content from the Course syllabus FDD3338 (Spring 2019–) are denoted with an asterisk ( )

Content and learning outcomes

Course contents

Subjects within computer vision in the research front-line.

Intended learning outcomes

After the course the student should be able to

* ) explain, implement and modify methods and algorithms within computer vision (the focus of the course can vary from time to time),

* ) contrast different methods against one another and choose appropriate method for a given problem (the focus of the course can vary from time to time).

Literature and preparations

Specific prerequisites

The student must carry out research on PhD level within computer vision or a close field.

Equipment

No information inserted

Literature

Kurslitteraturen väljs av examinator inför varje kurstillfälle.

Examination and completion

If the course is discontinued, students may request to be examined during the following two academic years.

Grading scale

P, F

Examination

  • EXA1 - Examination, 6.0 credits, grading scale: P, F

Based on recommendation from KTH’s coordinator for disabilities, the examiner will decide how to adapt an examination for students with documented disability.

The examiner may apply another examination format when re-examining individual students.

Other requirements for final grade

The requirements are decided by the examiner before each course offering.

Opportunity to complete the requirements via supplementary examination

No information inserted

Opportunity to raise an approved grade via renewed examination

No information inserted

Examiner

Ethical approach

  • All members of a group are responsible for the group's work.
  • In any assessment, every student shall honestly disclose any help received and sources used.
  • In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.

Further information

Course room in Canvas

Registered students find further information about the implementation of the course in the course room in Canvas. A link to the course room can be found under the tab Studies in the Personal menu at the start of the course.

Offered by

Main field of study

This course does not belong to any Main field of study.

Education cycle

Third cycle

Add-on studies

No information inserted

Postgraduate course

Postgraduate courses at EECS/Robotics, Perception and Learning